A method to control parameters of evolutionary algorithms by using reinforcement learning

Proceedings of the 6th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2010

Volumn , Issue , 2010, Pages 74-79

  Sakurai, Yoshitaka ^a   Takada, Kouhei ^a   Kawabe, Takashi ^a   Tsuruta, Setsuo ^a  

^a TOKYO DENKI UNIVERSITY   (Japan)

Author keywords

Delivery route scheduling system; Genetic algorithm (GA); Reinforcement learning; Traveling salesman problems (TSP)

Indexed keywords

ADAPTIVE PARAMETERS; CALCULATION COST; CONTROL PARAMETERS; DECISION RULES; MULTIPOINT SEARCH; OPTIMAL METHODS; OPTIMAL PARAMETER; OPTIMIZATION METHOD; OPTIMUM PARAMETERS; SCHEDULING SYSTEMS; SEARCH METHOD; SEARCH OPERATORS; SELECTION PROBABILITIES; TRAVELLING SALESMAN PROBLEM;

INTERNET; LEARNING ALGORITHMS; MATHEMATICAL OPERATORS; PARAMETER ESTIMATION; PROBLEM SOLVING; REINFORCEMENT LEARNING; TRAVELING SALESMAN PROBLEM; UNMANNED VEHICLES;

GENETIC ALGORITHMS;

EID: 79952556088     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SITIS.2010.22     Document Type: Conference Paper

References (16)

1. L. Davis, editor,: "Handbook of Genetic Algorithms", Van Nostrand Reinhold, N.Y., (1991).
2. D. Applegate, R. Bixby, V. Chvatal, and W. Cook, The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics): Princeton University Press, 2007.
3. Y. Sakurai, T. Onoyama, S. Kubota, S. Tsuruta: "A Multi-inner-world Genetic Algorithm using Multiple Heuristics to Optimize Delivery Schedule", Proc. of the 2009 IEEE International Conference on Systems, Man and Cybernetics (SMC 2009), Texas, USA, pp611-616, (2009.10).
4. Y. Sakurai, T. Onoyama, S. Kubota, S. Tsuruta: "A Multi-inner-world Genetic Algorithm to Optimize Delivery Problem with Interactive-time", Proc. of 4th IEEE Conference on Automation Science and Engineering (CASE 2008), Washington DC, USA, pp.583-590, (2008.8).
5. F. G. Lobo, C. F. Lima, and Z. Michalewicz, Parameter Setting in Evolutionary Algorithms: Springer Publishing Company, Incorporated, 2007.
6. Y. Sakurai, N. Honda, J. Nishino: "Acquisition of Knowledge for Gymnastic Bar Action by Active Learning Method", Journal of Advanced Computational Intelligence & Intelligent Informatics (JACIII), Vol.7, No.1, pp.10-18 (2003)
7. A. Eiben, Z. Michalewicz, M. Schoenauer, and J. Smith, "Parameter Control in Evolutionary Algorithms," in F.G. Lobo, C.F. Lima, Z. Michalewicz (eds.), Parameter Setting in Evolutionary Algorithms, Springer-Verlag, Berlin Heidlberg, 2007, pp. 19-46.
8. V. Nannen and A. E. Eiben, "A method for parameter calibration and relevance estimation in evolutionary algorithms," in Proceedings of the 8th annual conference on Genetic and evolutionary computation Seattle, Washington, USA: ACM, 2006.
9. L. DaCosta, A. Fialho, M. Schoenauer, Mich, and l. Sebag, "Adaptive operator selection with dynamic multi-armed bandits," in Proceedings of the 10th annual conference on Genetic and evolutionary computation Atlanta, GA, USA: ACM, 2008.
10. D. Thierens, "Adaptive Strategies for Operator Allocation," in F.G. Lobo, C.F. Lima, Z. Michalewicz (eds.), Parameter Setting in Evolutionary Algorithms, Springer-Verlag, Berlin Heidlberg, 2007, pp. 77-90.
11. J. E. Pettinger and R. M. Everson, "Controlling Genetic Algorithms With Reinforcement Learning," in Proceedings of the Genetic and Evolutionary Computation Conference: Morgan Kaufmann Publishers Inc., 2002.
12. Fei. Chen, Yang. Gao, Zhao-qian. Chen, and Shi-fu. Chen, "SCGA: Controlling Genetic Algorithms with Sarsa(0)," in Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on, 2005, pp. 1177-1183.
13. Yamamoto, Y., and Kubo, M., "Invitation to Traveling Salesman Problem", Asakura Syoten, Tokyo, 1997.
14. Nagata, Y. and Kobayashi, S., "The Proposal and Evaluation of a Crossover for Traveling Salesman Problems: Edge Assembly Crossover", Journal of Japan Society for AI, Vol.14, No.5, pp.848-859, 1999.
15. R. Sutton and A. Barto, Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning): Mit Pr, 1998.
16. Watkins C J C H and Dayan P., "Technical note: Qlearning," Machine Learning, Vol. 8(3-4), pp. 279-292, 1992